Tool Use for Early Detection of Cerebral Palsy: A Survey of Spanish Pediatric Physical Therapists
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to assess the use of diagnostic assessment tools in pediatric physical therapy practice in Spain. Best practice recommendations indicate the timely use of key assessment tools to reduce the age of diagnosis of cerebral palsy (CP). METHODS: Pediatric physical therapists currently working in Spain in early intervention were recruited through targeted physical therapy entities. They were invited to complete the purpose-developed electronic survey, consisting of 45 multiple-choice questions, with 5 thematic blocks. RESULTS: Results from 140 anonymous respondents were analyzed. The average reported age when CP was suspected was 12.6 months. Most used the child's clinical history (88.1%), the Alberta Infant Motor Scale (41.3%), and Vojta Assessment Procedure (32.1%) to assess and detect CP. General Movements Assessment (25.7%) and Hammersmith Infant Neurological Examination (28.4%) were used infrequently. CONCLUSIONS: Currently, pediatric physical therapists in Spain rely on clinical history and outdated tools to identify children with CP.Digital Abstract available at: http://links.lww.com/PPT/A361 (English).Digital Abstract available at: http://links.lww.com/PPT/A362 (Spanish).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".